{"id":7292,"date":"2019-07-23T11:06:27","date_gmt":"2019-07-23T10:06:27","guid":{"rendered":"https:\/\/www.brainlabsdigital.com\/?p=7292"},"modified":"2025-06-20T19:47:35","modified_gmt":"2025-06-20T19:47:35","slug":"what-is-a-ranking-factor","status":"publish","type":"post","link":"https:\/\/www.brainlabsdigital.com\/what-is-a-ranking-factor\/","title":{"rendered":"What is a ranking factor?"},"content":{"rendered":"

I decided to write this for a couple of reasons. One is that I\u2019ve seen a lot of potentially misleading Tweets on the subject recently (naming no names!), and the other is that it\u2019s related to another pet peeve of mine, about ranking factor studies<\/em>.<\/p>\n

What is a ranking factor?<\/h2>\n

A ranking factor is a variable that a search engine uses to decide the best ordering of relevant, indexed results returned for a search query.<\/p>\n

Note that I\u2019ve said the decision is between relevant<\/em>, indexed<\/em> pages – a good illustration of this distinction is the often absurdly high number shown beneath your query when you perform a Google search, such as the 643 million \u201cpotatoes<\/em>\u201d-related pages shown here:<\/p>\n

\"\"<\/p>\n

Most of these pages are not particularly<\/em> relevant, but this is the set that ranking factors are seeking to order. Some of the factors used to establish what is relevant to include in this list are also ranking factors (for example, having links with the anchor text \u201cpotatoes\u201d), but they are not the same thing.<\/p>\n

Perhaps the most famous ranking factor is Google\u2019s PageRank – invented at a time when, proportionately, a great deal more web browsing was done by clicking links from popular pages, the role of PageRank was to approximate the popularity, and therefore, by extension, authority, of a page on the internet.<\/p>\n

How are ranking factors combined?<\/h2>\n

A search algorithm might take ranking factors like PageRank and weight, sum, or multiply them in any way seen fit. The objective is to combine them in a way that achieves the \u201cbest\u201d results – for example, presenting the results that users are most likely to click on at the top. According to this CNBC interview<\/a> from late 2017, metrics Google might optimise for include time to SERP interaction <\/em>and rate of bouncing back to search results<\/em>.<\/p>\n

Amusingly, probably the best insight we\u2019ve had into how Google combines ranking factors came from a question about featured snippets, asked to Google\u2019s Gary Illyes by Jason Barnard earlier this year. I say amusingly<\/em> because Gary seemingly had no need to give such an in depth answer to this question, but the model he describes is fascinating to explore and extend upon – you can read more about it in Jason\u2019s article here<\/a>.<\/p>\n

What ranking factors are there?<\/h2>\n

We don\u2019t know! In fact, we don\u2019t even know how many there are. Probably a great many. (Although, not everything that influences rankings is a ranking factor – more on that below!)<\/p>\n

Google occasionally explicitly confirms a ranking factor (like HTTPS, or page loading times), but often this is as much as anything to push the SEO industry to change the internet in a direction they\u2019d like.<\/p>\n

It\u2019s in their interest to keep actual ranking factors and their relative importance very close to their chest, as their algorithm is part of their advantage over their competitors.<\/p>\n

Is user experience a ranking factor?<\/h2>\n

Not exactly, no – \u201cuser experience\u201d is not a metric. However, we do know (for example, from that CNBC article referenced above) that many of the things Google is looking for correlate with a good user experience. We also know that Google highlights things like slow loading times or excessively small font on mobile devices as SEO issues, which suggests an interest in this kind of factor.<\/p>\n

There\u2019s an ongoing debate about whether Google tries to measure this directly (for example, by looking at the click through rate of specific search results, compared to what might be expected, and adjusting their ranking on the fly), or whether they merely adjust their algorithm to look for things that correlate with user experience improvements. Many real world experiments suggest the former, but Google\u2019s official line is the latter.<\/p>\n

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It\u2019s in their interest to keep actual ranking factors and their relative importance very close to their chest, as their algorithm is part of their advantage over their competitors.<\/p>\n<\/blockquote>\n

Misconceptions<\/h2>\n

Misconception 1: All metrics that correlate with rankings are ranking factors<\/h3>\n

This misconception is probably in some small part my fault – and also the fault of others who, like me, have published so called ranking factor studies<\/em>. These are actually correlation studies – we can look at what qualities are typically held by well-ranking pages, but this does not mean that those qualities are necessarily ranking factors. Facebook Likes, for example, correlate well with Google rankings. There are a few possible explanations for this:<\/p>\n